The city-building merging algorithm is important in automated generalization of large-scale map.After discussing the shortcomings of current algorithms

a new method based on the technique of agent

TIN and clustering is put forward

which is expected to improve the operation speed

intelligentized and roboticized level of generalization.First

a clustering analysis with map data is done in order to divide whole data into several parts.Second

this algorithm regards Delaunay triangle as its basic technology

and takes a new classifying criterion to it.Third

based on the TIN classifying

an agent layer is expressed.And for every different agent layers

different agent life cycles and data structures are defined.Finally

as the final goal

a new algorithm is evolved from the techniques of agent

TIN technique of graphics calculation

and the map generalization constrains.An example and relevant analysis are presented in the end.The result shows that this algorithm is more excellent than others not only in functions but also in the speed

intelligence and automatization level.On the other hand

some modification to the algorithm is discussed.